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| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -0,0 +1,62 @@ | ||
| # -*- coding: utf-8 -*- | ||
| """ | ||
| @desc: 新浪 | ||
| https://vip.stock.finance.sina.com.cn/mkt/#hskzz_z | ||
| @author: 1nchaos | ||
| @time:2023/4/5 | ||
| @log: | ||
| """ | ||
| import pandas as pd | ||
|
|
||
| from adata.bond.market.bond_market_template import BondMarketTemplate | ||
| from adata.common.utils import requests | ||
|
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||
|
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| class BondMarketSina(BondMarketTemplate): | ||
| """bond 行情""" | ||
|
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| def __init__(self) -> None: | ||
| super().__init__() | ||
|
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| def list_market_current(self, code_list=None): | ||
| """ | ||
| 获取新浪的最新可转债行情 | ||
| url : http://vip.stock.finance.sina.com.cn/quotes_service/api/json_v2.php/Market_Center.getHQNodeDataSimple | ||
| :param code_list: 可转债代码列表 | ||
| :return: 最新行情数据 | ||
| """ | ||
| # 0.进行参数拼接处理 | ||
| api_url = f"http://vip.stock.finance.sina.com.cn/quotes_service/api/json_v2.php/Market_Center.getHQNodeDataSimple" | ||
|
|
||
| # 2.循环请求 | ||
| data = [] | ||
| for i in range(100): | ||
| # 1.请求接口 | ||
| params = {"page": {i+1}, "num": "80", "sort": "symbol", | ||
| "asc": "1", "node": "hskzz_z", "_s_r_a": "page"} | ||
| res = requests.request('get', api_url, params=params) | ||
| res = res.json() | ||
| data.extend(res) | ||
| if len(res) < 80: | ||
| break | ||
| # 3. 结果筛选 | ||
| if code_list is not None: | ||
| new_data = [] | ||
| for d in data: | ||
| if d['code'] in code_list: | ||
| new_data.append(d) | ||
| data = new_data | ||
| # 4. 封装数据 | ||
| rename = {'code': 'bond_code', 'name': 'bond_name', 'pricechange': 'change', 'changepercent': 'change_pct', | ||
| 'settlement': 'pre_close', 'ticktime': 'time', 'trade': 'price'} | ||
| result_df = pd.DataFrame(data=data).rename(columns=rename) | ||
| columns_to_convert = ['price', 'open', 'high', 'low', 'pre_close', 'change', 'change_pct', 'volume', 'amount'] | ||
| result_df[columns_to_convert] = result_df[columns_to_convert].astype(float) | ||
| result_df_unique = result_df.drop_duplicates(keep='last', subset=['bond_code']) | ||
| return result_df_unique[self._MARKET_CURRENT_COLUMNS] | ||
|
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|
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| if __name__ == '__main__': | ||
| df = BondMarketSina().list_market_current(code_list=['110044', '127103']) | ||
| print(df) |
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| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -0,0 +1,24 @@ | ||
| # -*- coding: utf-8 -*- | ||
| """ | ||
| @desc: readme | ||
| @author: 1nchaos | ||
| @time: 2024/05/05 | ||
| @log: change log | ||
| """ | ||
|
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||
|
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| class BondMarketTemplate(object): | ||
| """ | ||
| 债券行情 | ||
| """ | ||
| _MARKET_CURRENT_COLUMNS = ['bond_code', 'bond_name', 'price', 'open', 'high', 'low', 'pre_close', 'change', | ||
| 'change_pct', 'volume', 'amount', 'time'] | ||
|
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| def list_market_current(self, code_list=None): | ||
| """ | ||
| 获取多个可转债的最新行情信息 | ||
| :param code_list: 可转债代码 | ||
| :return: 当前最新的行情价格信息 | ||
| _MARKET_CURRENT_COLUMNS | ||
| """ | ||
| pass |
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| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -0,0 +1,103 @@ | ||
| # -*- coding: utf-8 -*- | ||
| """ | ||
| @desc: 热点榜单 TODO | ||
| 同花顺热点榜单 | ||
| https://eq.10jqka.com.cn/frontend/thsTopRank/index.html?fontzoom=no&client_userid=ceZLR&share_hxapp=gsc&share_action=webpage_share.hot_list_1714369375634&back_source=wxhy#/ | ||
| @author: 1nchaos | ||
| @time: 2024/4/29 | ||
| @log: change log | ||
| """ | ||
| import pandas as pd | ||
|
|
||
| from adata.common.base.base_ths import BaseThs | ||
| from adata.common.headers import ths_headers | ||
| from adata.common.utils import requests | ||
|
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|
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| class Hot(BaseThs): | ||
| """热门榜单""" | ||
|
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||
| # 东方财富人气榜 | ||
| def pop_rank_100_east(self): | ||
| """ | ||
| 东方财富人气榜100 | ||
| http://guba.eastmoney.com/rank/ | ||
| """ | ||
| # 1.url | ||
| url = "https://emappdata.eastmoney.com/stockrank/getAllCurrentList" | ||
|
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||
| # 2. 请求数据 | ||
| params = {"appId": "appId01", "globalId": "786e4c21-70dc-435a-93bb-38", | ||
| "marketType": "", "pageNo": 1, "pageSize": 100, } | ||
| res = requests.request(method='post', url=url, json=params).json() | ||
| df = pd.DataFrame(res["data"]) | ||
|
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| df["mark"] = ["0" + "." + item[2:] if "SZ" in item else "1" + "." + item[2:] | ||
| for item in df["sc"]] | ||
| ",".join(df["mark"]) + "?v=08926209912590994" | ||
| params = {"ut": "f057cbcbce2a86e2866ab8877db1d059", | ||
| "fltt": "2", "invt": "2", "fields": "f14,f3,f12,f2", | ||
| "secids": ",".join(df["mark"]) + ",?v=08926209912590994", } | ||
| url = "https://push2.eastmoney.com/api/qt/ulist.np/get" | ||
| res = requests.request(method='get', url=url, params=params) | ||
|
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||
| # 3. 解析封装数据 | ||
| data = res.json()["data"]["diff"] | ||
| rename = {'f2': 'price', 'f3': 'change_pct', 'f12': 'stock_code', 'f14': 'short_name', } | ||
| rank_df = pd.DataFrame(data).rename(columns=rename) | ||
| rank_df["change_pct"] = pd.to_numeric(rank_df["change_pct"], errors="coerce") | ||
| rank_df["price"] = pd.to_numeric(rank_df["price"], errors="coerce") | ||
| rank_df["change"] = rank_df["price"] * rank_df["change_pct"] / 100 | ||
| rank_df["rank"] = range(1, len(rank_df) + 1) | ||
| return rank_df[["rank", "stock_code", "short_name", "price", "change", "change_pct"]] | ||
|
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||
| def hot_rank_100_ths(self): | ||
| """ | ||
| 同花顺热股100 | ||
| https://dq.10jqka.com.cn/fuyao/hot_list_data/out/hot_list/v1/stock?stock_type=a&type=hour&list_type=normal | ||
| """ | ||
| api_url = 'https://dq.10jqka.com.cn/fuyao/hot_list_data/out/hot_list/v1/stock?stock_type=a&type=hour&list_type=normal' | ||
| headers = ths_headers.json_headers | ||
| headers['Host'] = 'dq.10jqka.com.cn' | ||
| res = requests.request(method='get', url=api_url, params={}, headers=headers) | ||
| data = res.json()['data']['stock_list'] | ||
| data_list = [] | ||
| for d in data: | ||
| d['concept_tag'] = ";".join(d['tag']['concept_tag']) | ||
| if 'popularity_tag' in d['tag']: | ||
| d['pop_tag'] = d['tag']['popularity_tag'].replace('\n', '') | ||
| data_list.append(d) | ||
| rename = {'order': 'rank', 'rise_and_fall': 'change_pct', 'code': 'stock_code', 'name': 'short_name', | ||
| 'rate': 'hot_value', 'concept_tag': 'concept_tag'} | ||
| rank_df = pd.DataFrame(data).rename(columns=rename) | ||
| rank_df = rank_df[["rank", "stock_code", "short_name", "change_pct", "hot_value", "pop_tag", "concept_tag"]] | ||
| return rank_df | ||
|
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||
| def hot_concept_20_ths(self, plate_type=1): | ||
| """ | ||
| 同花热门概念板块 | ||
| :param plate_type: 1.概念板块，2.行业板块；默认：概念板块 | ||
| """ | ||
| plate_type = 'concept' if plate_type == 1 else 'industry' | ||
| api_url = f'https://dq.10jqka.com.cn/fuyao/hot_list_data/out/hot_list/v1/plate?type={plate_type}' | ||
| headers = ths_headers.json_headers | ||
| headers['Host'] = 'dq.10jqka.com.cn' | ||
| res = requests.request(method='get', url=api_url, params={}, headers=headers) | ||
| data = res.json()['data']['plate_list'] | ||
| data_list = [] | ||
| for d in data: | ||
| data_list.append(d) | ||
| rename = {'order': 'rank', 'rise_and_fall': 'change_pct', 'rate': 'hot_value', 'code': 'concept_code', | ||
| 'name': 'concept_name'} | ||
| rank_df = pd.DataFrame(data).rename(columns=rename) | ||
| rank_df = rank_df[["rank", "concept_code", "concept_name", "change_pct", "hot_value", "hot_tag"]] | ||
| return rank_df | ||
|
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||
|
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| if __name__ == '__main__': | ||
| print(Hot().hot_rank_100_ths()) | ||
| print(Hot().pop_rank_100_east()) | ||
| print(Hot().hot_concept_20_ths(plate_type=1)) | ||
| print(Hot().hot_concept_20_ths(plate_type=2)) |
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